Shazam! How the music industry hears what you (will) love

At some point in 2014, your friends are totally going to be into this Dutch DJ named Martin Garrix. Or maybe your son will be into a young rapper named Rich Homie Quan. Or maybe your girlfriend will be humming tunes from Australian songwriter Vance Joy.

The predictions around these relative unknowns are according to data from Shazam. The company employs a nifty smartphone app that solves the “What’s the name of this song again?” problem. Tap it on, point your phone toward the speaker and the software tells you the name of the tune.

But this makes Shazam much more than a party trick: it’s an ear to the ground for the music industry. Because most times, people search for a title and artist because they really like the song.

“This helps it be a pure measurement,” says Daniel Danker, Shazam’s chief product officer. He says partnerships with the music and radio industry in this regard aren’t an integral part of Shazam’s business — yet. “These are early days.”

The idea is that when a tune surfaces, say, for the soundtrack of a new show, the company can measure in real time as people hold their phones to the television. Ben Howard’s “Oats in the Water” generated 300,000 Shazam searches all at once when it aired on The Walking Dead. That kind of blip gets flagged in Shazam’s system. Knowing that people were moved enough to get out their phone to get the name — at that very instant — provides powerful data for music marketers.

Soundhound is a direct competitor to Shazam. “Data and analytics are highly valued, given where we sit in the ecosystem,” says Katie McMahon Soundhound’s vice president of sales and marketing. “This is a heat map of how people are responding to the music they’re hearing.”

Otherwise, a listening sample over a certain time period might not show artists like Garrix, Quan and Joy standing out against others. Shazam feels comfortable predicting popularity increases because data shows people scan those artists’ songs at a statistically-significantly higher rate. That data instructs radio stations and the music industry where to invest playing time and advertising budgets.

Shazam is far from the only digital data source for the music industry. Streaming services report play counts, discussion on Twitter has become somewhat measurable and you can always tally “likes” on Facebook. It also has a strong competitor in Santa Clara-based Soundhound and, since this is search afterall, a company called Google quietly released its version of a sound scanning app about a year ago.

Google’s app still only has around 5 million downloads but Shazam and Soundcloud are up over 50 million downloads in the Android store. And both have filed a number of patents regarding audio recognition technology. I primarily use Soundhound since, for me, it nails the song a bit more often. But you’d be splitting hairs to say there’s that much of a difference between the two, save one: Soundhound allows you to hum a tune to find a song. Shazam does not.

McMahon notes that this creates a slightly different user case; the song is catchy and powerful (and played) enough to have imprinted on someone’s brain. In 2012 “Someone Like You” by Adele topped Soundhound’s “sing-hum query” list, as the algorithm is known.

But once a song is matched, both companies take a sales commission should the user buy it through the service. Danker says Shazam sells about 500,000 tracks each day. Yet people may increasingly stream the song off Spotify, Rdio or Google All Access. Twenty million listeners had music subscription services in 2012, a 44 percent increase over 2011, according to data from the International Federation of the Phonographic Industry (IFPI) which represents the recording industry worldwide.

So data analysis and predictions also become an alluring path to profits. Outsiders have taken note. Mexican business mogul and former richest man in the world Carlos Slim Helú,invested $40 million in Shazam in July.

Granted, Shazam’s list of eventually popular artists does fall down in a pretty obvious way: Many of the songs that will be popular in 2014 haven’t been released yet. But “we can kind of guess the top 40 list about 40 days in advance,” Danker says, noting that data is “a currency” for the music industry. “Over time you’ll see new business models emerge out of that.”

A scatter plot of sonic peaks for a song over time. This “fingerprint” is typically unique for each song, making it simpler to search for.

Analysis can be far more specific than probable hits: Shazam knows which artists catch your fancy and can sell their next hit or tickets the next time they are coming to town — and take a commission.

To many, that behind-the-curtains work feels uncomfortable — one more avenue where a big brother is monitoring our habits in order to make money. Like most apps, Shazam is another tradeoff in the never ending convenience versus privacy debate — though compared to other privacy transgressions, knowing your favorite dance song seems trivial.

Shazam works because every song generates something like a “fingerprint” — the collective dancing of the red-yellow-green bars of an equalizer (the various frequencies) as you listen. Shazam stores that fingerprint for tens of millions of songs, and then matches (or tries to) with what’s coming out of the speaker.

However, encoding the entire fingerprint — spectrogram, as it’s technically known — would be too labor intensive. Avery Li-Chun Wang, one of the company’s co-founders, explained in a paper that instead the software simply looks for the big peaks and valleys of sound and remembers those. That greatly reduces the search workload and means that occasionally a song will match in less than a few seconds.

But this doesn’t always work smoothly. If you’re in a crowded bar, the app will have trouble sifting through the noise.

Regardless, the fingerprints of those hits could be used to project what will be popular in the future, before people start searching, just by looking at the song construction. We know that there are certain qualities like tempo, key and melody line that will make a song good.

But Danker says Shazam shies from operating that way. The new Daft Punk hit “Get Lucky”, he says, was not like anything the group had done in the past and had a disco feel that hadn’t been too popular for decades. “The danger with recommendation engines is that you tend to get more of the same,” he says “It can be limiting in that scenario.”